Study On The Control Method Of Autonomous Navigation System Of Intelligent Self-propelled Hot Fog Machine Based On Lidar

As a popular direction of agricultural machinery in the future,agricultural robot is gradually developing toward s the direction of autonom ous navigation.Navigation system is an important core system of agricultural robot.In-depth research on it is not only for agricultural robot to realize autonomous walking in com plex farmland environment,but also for agricultural robot to realize accurate operation.In this paper,aiming at the problem of autonomous navigation of agricultural robots in the high-stalk crop environment,an intelligent self-propelled hot fog machine autonomous navigation control method based on lidar is designed by using the first-line lidar as the navigation equipment.The main research contents are as follows:(1)LMS111-10100 lidar was used to collect the point cloud data in the corn field,analyze the point cloud data collected in the corn field,and extract effective information.(2)The improved k-means clustering algorithm is proposed to extract inter-row information of crops.RANSAC algorithm was used to build crop environment model.The least square method is used for navigation path fitting.MATLAB software was used to process lidar poi nt cloud data of two different crop types of photinia and maize,showing the navigation paths under the two crop environments.(3)The autonomous navigation system sof tware of intelligent self-propelled hot fog machine based on lidar is designed,and the hardware of intelligent self-propelled hot fog machine and the lower one is developed.(4)The autonomous navigation test of the intelligent self-propelled hot f og machine was carried ou t.Three different walking environments,namely,linear,lshaped and u-shaped,were artificially constructed under the soil and cement pavement.The experimental data of the intelligent se lf-propelled hot fog m achine,such as th e triaxial speed and lateral deviation,were measured as the navigation perform ance indicators,and the exp erimental results were analyzed.When walking at th e initial speed of 0.2m/s,the m ean lateral deviation in the lin ear and l-sha ped walking environment of soil was 4.39 cm and 4.15 cm respectively,and the mean lateral deviation in the linear and l-shaped walking e nvironment of ce ment was 3.8c m and 5.36 cm respectively.When walking at the initial speed of 0.4m/s,the average lateral deviation in the linear and l-shaped walking environment of soil was 5.26 c m and 4.3c m respectively,and the av erage lateral devi ation in the lin ear and l-sha ped walking environment of cement was 5.1cm and 6.7cm respectively.The test results show that the intelligent self-propelled hot fog machine can basically realize autonomous navigation.When walking at a low speed of 0.2m /s,the lateral deviation value is sm all and the velocity value in the X/Y/Z direction fluctuates little.